Evidence map›Paper›PMID 38918363›Full record

ArticleLight, science & applications2024

EventLFM: event camera integrated Fourier light field microscopy for ultrafast 3D imaging.

Ruipeng Guo, Qianwan Yang, Andrew S Chang, Guorong Hu, Joseph Greene, Christopher V Gabel, Sixian You, Lei Tian

Abstract read
In one paragraph

Article in Light, science & applications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Dual-Channel Event Microscopy for Ultrafast Biological Imaging.bioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. Ultra-fast light-field microscopy with event detection.Light, science & applications · 2024
    Article
  15. Model-Based Explainable Deep Learning for Light-Field Microscopy Imaging.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ruipeng GuoDepartment of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
Qianwan YangDepartment of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
Andrew S ChangDepartment of Physiology and Biophysics, Boston University, Boston, MA, 02215, USA.
Guorong HuDepartment of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
Joseph GreeneDepartment of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA.
Christopher V GabelDepartment of Physiology and Biophysics, Boston University, Boston, MA, 02215, USA.
Sixian YouResearch Laboratory of Electronics (RLE) in the Department of Electrical Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Lei TianDepartment of Electrical and Computer Engineering, Boston University, Boston, MA, 02215, USA. leitian@bu.edu.ORCID http://orcid.org/0000-0002-1316-4456

Funding

Computational Miniature Mesoscope for Cortex-wide, Cellular resolution Ca2+ Imaging in Freely Behaving MiceR01NS126596 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI Lei Tian · 2022 to 2026
$2.0M
NINDS NIH HHS R01 NS126596Silicon Valley Community Foundation (SVCF) 5022U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01NS126596
6 · The paper itself

Abstract

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes. Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product (SBP). Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems, thus restricting data throughput to maintain high SBP at limited frame rates. To address this, we introduce EventLFM, a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy (LFM), a state-of-the-art single-shot 3D wide-field imaging technique. The event camera operates on a novel asynchronous readout architecture, thereby bypassing the frame rate limitations inherent to conventional CMOS systems. We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM. Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates. Furthermore, we highlight EventLFM's capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C. elegans. We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

Identifiers

PMID38918363
PMCPMC11199625

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.